USING THE EXPECTATION OR THE DISTRIBUTION OF THE IDENTITY BY DESCENT FOR MAPPING QUANTITATIVE TRAIT LOCI UNDER THE RANDOM MODEL

We examine the ability of four implementations of the random model to map quantitative trait loci (QTLs). The implementations use either the expectation or the distribution of the identity-by-descent value at a putative QTL and either a 2 x 1 vector of sib-pair traits or their sc alar difference. When the traits of both sibs are used, there as littl e difference between the expectation and distribution methods, while t he expectation method suffers in both precision and power when the dif ference between traits is used. This is consistent with the prediction that the difference between the expectation and distribution methods is inversely proportional to the amount off information available for mapping. We iind, though, that the amount of information must be very low for this difference to be noticeable. This is exemplified when bot h marker loci are fixed. In this case, while the expectation method is powerless to detect the QTL, the distribution method can still detect the presence (but nor the position) of the QTL 59% of the time (when using trait values) or 14% of the time (when using trait differences). We also note a confounding between estimates of the QTL, polygenic, a nd error variance. The degree of confounding is small when the vector ok trait values is used but can be substantial when the expectation me thod and trait differences are used. We discuss this in light of the g eneral ability of the random model to partition these components.